Research On Abnormal Medical Insurance Data Mining Method Based On BP Neural Network

In recent years,the occurrence of abnormal medical insurance consumption cases in the global intensified,as a result,the fund of a large number of national social security institutions health insurance has been lost.Abnormal medical insurance consumption is not only not conducive to the construction of national moral integrity,but also affects the fair implementation of national health insurance laws and regulations as well as the effective use of health insurance funds.The appearance of abnormal medical insurance consumption cases has seriously hindered the sustainable development of medical insurance in China.Therefore,how to quickly identify abnormal medical insurance consumption cases and formulate effective solutions has become a valuable research topic in the academic world.However,at present,the researches of Chinese scholars are mainly focused on the construction of health insurance laws and regulations and the perfection of various supervision systems.The research on using scientific and technological means to solve this problem is relatively rare,based on this background,this paper attempts to adopt BP neural network algorithm to study abnormal health insurance consumption data.The research focus of this paper is how to identify the abnormal medical insurance consumption behavior quickly and effectively.We shall conclude the abnormal form of medical insurance consumption behavior and the relevant policies and regulations used in our country to guard against abnormal transactions first,and sum up by collecting a large number of existing abnormal consumption cases so as to find out the law of these abnormal consumption behaviors,analyze the behavior characteristics of common abnormal consumption behavior on the data level,and take this as the basis of abnormal consumption behavior detection.Thus,the abnormal medical insurance consumption detection model using BP neural network algorithm is designed.Then the massive data are extracted from the current health insurance system as input and test samples,input samples are input into the neural network model for training and learning,and the test samples are tested to verify the predictability of the test model completed by the training.Finally,the output values are analyzed and some suggestions are put forward.The results show that BP neural network algorithm is an algorithm means to effectively identify abnormal medical insurance consumption behavior.In addition,detailed analysis and explanation have been conducted from the perspective of the characteristics and rules of abnormal behavior in medical insurance,which has a certain reference for social security agencies to enhance the identification ability and technology of abnormal consumption behaviors.